openvinotoolkit/training_extensions/pytorch_toolkit/instance_segmentation/ converting to onnx

[DanielSerna]

Hello intel team,

I've used openvinotoolkit/training_extensions/pytorch_toolkit/instance_segmentation/ to train an instance segmentation model with the following command:

python3 tools/train.py --dataset coco2017 --max_image_size 480 640 --bs 8 --bs_per_gpu 2 --lr 0.02 --max_iter 1000 --drop_lr 60000 80000 --model segmentoly.rcnn.model_zoo.resnet_fpn_mask_rcnn.ResNeXt152FPNMaskRCNN --load_backbone data/pretrained_models/converted/imagenet/detectron/resnext152.pth

but when I try to convert to onnx with the script provided in the training extensions:

python3 tools/convert_to_onnx.py --model segmentoly.rcnn.model_zoo.resnet_fpn_mask_rcnn.ResNeXt152FPNMaskRCNN --ckpt outputs/MaskRCNN/Oct28-21-05-30/ckpt/model_step_1000.pth --input_size 480 640 -nc 2 --show_flops --output_file openvino_mrcnn.onnx

I get the following error:

RuntimeError: tuple appears in op that does not forward tuples, unsupported kind: prim::PythonOp (VisitNode at /pytorch/torch/csrc/jit/passes/lower_tuples.cpp:135)

In some pytorch forums I read that it could be because of the DataParallel used in the training, I've changed it but got the same result.

any idea what it could be ?

Thanks in advance.

[Iffa_Intel]

Greetings,

From the source that you were referring, it seems that these are validated with:

• Ubuntu* 16.04
• Python* 3.5.2
• PyTorch* 0.4.1
• OpenVINO™ 2019 R1 with Python API

I'm not sure whether if you are using newer versions of any of this would be the cause.

Anyway, you can cross check your steps with this: https://www.youtube.com/watch?v=wmRNqg_7Eo0

Sincerely,

Iffa

[Iffa_Intel]

In addition to that, try to run the demo on their PyTorch model and then do the evaluation.

Command examples are below.

$ python3 tools/demo.py \

--dataset coco_2017_val \

--ckpt data/pretrained_models/converted/coco/detectron/mask_rcnn_resnet50_fpn_2x.pth \

--mean_pixel 102.9801 115.9465 122.7717 \

--fit_window 800 1333 \

--video 0 \

--delay 1 \

--show_fps \

pytorch \

--model segmentoly.rcnn.model_zoo.resnet_fpn_mask_rcnn.ResNet50FPNMaskRCNN \

--show_flops

$ python3 tools/test.py \

--dataset coco_2017_val \

--ckpt data/pretrained_models/converted/coco/detectron/mask_rcnn_resnet50_fpn_2x.pth \

--mean_pixel 102.9801 115.9465 122.7717 \

--fit_max 800 1333 \

pytorch \

--model segmentoly.rcnn.model_zoo.resnet_fpn_mask_rcnn.ResNet50FPNMaskRCNN \

--show_flops

Also, the workaround for DataParallel from PyTorch forums as OpenVINO here just utilizes PyTorch capabilities might be correct. Please see this topic https://github.com/pytorch/pytorch/issues/13397

Sincerely,

Iffa

[Iffa_Intel]

Greetings,

Intel will no longer monitor this thread since we have provided a solution. If you need any additional information from Intel, please submit a new question.

Sincerely,

Iffa